Main results 👍
- Performance: Generated code can be highly optimized for a specific task, as it doesn’t need to carry the overhead of conditional logic for other scenarios.
Department of Statistical Science, UCL
Resources
Slides and code here: github.com/n8thangreen/data-science-in-health-talk
Health literacy is broadly defined as the ability to access, understand, appraise, and communicate health information, enabling individuals to engage in healthcare and maintain good health throughout their lives.
UCL Public Policy Fellowship
Newham Residents Survey 2023 (NRS)
Skills for Life Survey 2011
Additional data
The predicted probability \(\hat{\pi}_i\) is defined as: \[ \hat{\pi}_i = \text{logit}^{-1} \left( \hat{\beta}_0 + \sum_{x} \hat{\beta}^{x}_{\gamma_x[i]} \right) \]
where \(\hat{\beta}_0\) is the intercept, \(\hat{\beta}^{x}_{\gamma_x[i]}\) are coefficients for covariates \(x\) (age, sex, eng, white, ukborn, qual, inc, job, work, home), and \(\gamma_x[i]\) represents the level or category for covariate \(x\) for individual \(i\). IMD is included as multilevel random effects \(\beta^{\text{IMD}}_j \sim \text{N}(\mu_{\text{IMD}}, \sigma_{\text{IMD}}^2)\). Priors distributions for fixed effects are normal distributions centered at zero with modest variance, and half-normal priors are used for random effect standard deviations .
The health literacy probabilities for each demographic category (cell \(c\)) are weighted by their proportion in the actual Newham population. With 11 covariates resulting in \(|\mathcal{S}|\) = 13,824 cells, the post-stratified estimate \(\hat{\pi}^{\text{mrp}}\) is: \[ \hat{\pi}^{\text{mrp}} = \sum_{c = 1}^{|\mathcal{S}|} w_c \hat{\pi}_{c} \] where \(\mathcal{S}\) is the set of all covariate combinations, \(N_c\) is the population frequency for cell \(c\), \(N\) is the total population size, and \(w_c = N_{c} / N\) are the combination weights.
Reference
Green, N., Kurt, M., Moshyk, A., Larkin, J. and Baio, G. (2025), A Bayesian Hierarchical Mixture Cure Modelling Framework to Utilize Multiple Survival Datasets for Long-Term Survivorship Estimates: A Case Study From Previously Untreated Metastatic Melanoma. Statistics in Medicine, 44: e70132. https://doi.org/10.1002/sim.70132
Nathan Green | UCL | n.green@ucl.ac.uk